Murine Chronomes

Time plots of original values (dots) of variables such as blood eosinophils (E) (Figure 1/I, left) or glycogen content (Figure 1/III, left) reveal great variability, confusing at first, until the data are processed by relatively simple statistical techniques such as averaging and stacking over an idealized 24-hour span corresponding to an anticipated periodicity. Once this is done and the results are displayed as a function of time, they show the time-macroscopic ubiquity of circadians. The data averaging for different hours of the day also reveals differences in the time course (in phase) of different functions of a given organ such as the liver (Figure 1/VC; see also Figure 2/III), of cell division (mitosis) in different organs and tissues (Figure 1/VB) and of different variables at the level of the body as a whole (Figure 1/VA and D). The structure of the circadian system becomes apparent by the application of the methods of chronobiometry: the circadian variation in blood eosinophils determined years apart in two laboratories as far apart as Minnesota and Maine is closely reproduced (Figure 1/I, right). The lawfulness of the circadian variation yielded by the application of chronobiologic techniques is also revealed for the drastic changes in liver glycogen content (Figure 1/III, middle). In this case, a circadian rhythm in the liver's glycogen is seen to persist under conditions of starvation and dehydration, with little if any alteration in the dynamic rhythm characteristics, as compared to usual ad lib conditions, once the data are expressed as a percentage of the overall mean, Figure 1/III, right.

After a prominent circadian rhythmicity was found at different levels of organization, several series of experiments were carried out under rigorously standardized laboratory conditions in order to investiga+e the effect of a single physical stimulus such as exposure to noise. Outcomes were as different as no response, convulsion or even death, as a function of the circadian stage at which the organism was exposed to noise. Whether the stimulus was audiogenic or the exposure to an endotoxin, or to a drug such as ouabain, or to whole-body irradiation, predictable changes were found as a function of the circadian stage at which the stimulus was applied, albeit with differences in the timing of these susceptibility-resistance rhythms to different agents. The hours of changing resistance were thus uncovered, and the times of overall largest response by the organism to a fixed stimulus applied at different rhythm stages mapped (Figure I/VD). Applications followed (Figure 1/IV). Prominent susceptibility rhythms were documented in the experimental laboratory, as illustrated here for the case of the mortality from agents affecting the central nervous system and for the case of the survival from (tolerance of) toxic doses of anticancer drugs. In each case, the nonoverlap by the elliptical 95% confidence region of the center of the circular plot (pole) can be interpreted as the presence of a statistically significant circadian rhythm in the susceptibility of the organism to each of these different agents. The orientation of the directed line (vector) indicates the time of acrophase, that is the time of the largest anticipaed response. Such charts are helpful in guiding the timing of the administration of the various agents so mapped. The chronotherapy of cancer is one critical application resulting from this work.